Abstract

One of the most challenging problems facing builders and facilitators of community networks is to create and sustain social engagement among members. In this paper, we investigate the drivers of social engagement in a community network through the analysis of three data sources: activity logs, a member survey, and the content analysis of the conversation archives. We describe three important ways to encourage and support social engagement in online communities: through system design elements such as conversation channeling and event notification, ...

Abstract

Operators of online social networks are increasingly sharing potentially sensitive information about users and their relationships with advertisers, application developers, and data-mining researchers. Privacy is typically protected by anonymization, i.e., removing names, addresses, etc. We present a framework for analyzing privacy and anonymity in social networks and develop a new re-identification algorithm targeting anonymized social-network graphs. To demonstrate its effectiveness on real-world networks, we show that a third of the users who can be verified to have accounts on both Twitter, a popular microblogging service, and Flickr, an online ...

Abstract

Online social networking sites like Orkut, YouTube, and Flickr are among the most popular sites on the Internet. Users of these sites form a social network, which provides a powerful means of sharing, organizing, and finding content and contacts. The popularity of these sites provides an opportunity to study the characteristics of online social network graphs at large scale. Understanding these graphs is important, both to improve current systems and to design new applications of online social networks. This paper presents ...

Abstract

Online social networking sites like MySpace, Orkut, and Flickr are among the most popular sites on the Web and continue to experience dramatic growth in their user population. The popularity of these sites offers a unique opportunity to study the dynamics of social networks at scale. Having a proper understanding of how online social networks grow can provide insights into the network structure, allow predictions of future growth, and enable simulation of systems on networks of arbitrary size. However, to date, ...

Abstract

Our contribution wants to encourage a discussion about the very basic assumptions behind the design of social networking systems and suggest that reputation and trust are not objective quantities on which everyone can and should agree but instead reflections of subjective and personal beliefs that might differ among different people. This latter assumption should guide the design of online systems powered by the next generation electronic identities. ...

Abstract

Search engines like Google.com use the link structure of the Web to determine whether Web pages are authoritative sources of information. However, the linking mechanism provided by HTML does not allow the Web author to express different types of links, such as positive or negative endorsements of page content. As a consequence, search engine algorithms cannot discriminate between sites that are highly linked and sites that are highly trusted. We demonstrate our claim by running PageRank on a real world data ...

Abstract

Recommender Systems based on Collaborative Filtering suggest to users items they might like, such as movies, songs, scientific papers, or jokes. Based on the ratings Based on the ratings provided by users about items, they first find users similar to the users receiving the recommendations and then suggest to her items appreciated in past by those like-minded users. However, given the ratable items are many and the ratings provided by each users only a tiny fraction, the step of finding similar ...

Abstract

In this paper we give models and algorithms to describe and analyze the collaboration among authors of Wikipedia from a network analytical perspective. The edit network encodes who interacts how with whom when editing an article; it significantly extends previous network models that code author communities in Wikipedia. Several characteristics summarizing some aspects of the organization process and allowing the analyst to identify certain types of authors can be obtained from the edit network. Moreover, we propose several indicators characterizing the ...

Abstract

The paper offers a framework to explain large scale effective practices of sharing private, excludable goods. It starts with case studies of distributed computing and carpooling as motivating problems. It then suggests a definition for “shareable goods” as goods that are lumpy and mid-grained in size, and explains why goods with these characteristics will have systematic overcapacity relative to the requirements of their owners. The paper then uses comparative transaction costs analysis, focused on information characteristics in particular, ...

Note (first note only)

Best paper, ever!

Abstract

The problem of sustaining a public resource that everybody is free to overuse—the 'tragedy of the commons'1, 2, 3, 4, 5, 6, 7—emerges in many social dilemmas, such as our inability to sustain the global climate. Public goods experiments4, which are used to study this type of problem, usually confirm that the collective benefit will not be produced. Because individuals and countries often participate in several social games simultaneously, the interaction of these games may provide a sophisticated way by which ...

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that the need to maintain reputation for indirect reciprocity maintains contributions to the public good at an unexpectedly high level. But if rounds of indirect reciprocation are not expected, then contributions to the public good drop quickly to zero. Alternating the games leads to higher profits for all players. As reputation may be a currency that is valid in many social games, our approach could be used to test social dilemmas for their solubility.

Abstract

The asymmetry of activity in virtual communities is of great interest. While participation in the activities of virtual communities is crucial for a community's survival and development, many people prefer lurking, that is passive attention over active participation. Often, lurkers are the vast majority. There could be many reasons for lurking. Lurking can be measured and perhaps affected by both dispositional and situational variables. This project investigates social and cultural capital, situational antecedents of lurking and de-lurking. We propose a novel ...

Abstract

Environments with public goods are a wonderful playground for those interested in delicate experimental problems, serious theoretical challenges, and difficult mechanism design issues. In this chapter I will look at one small but fundamental part of the rapidly expanding experimental research. In Section 1, I describe a very simple public good experiment - what it is, what some theories predict, what usually happens, and why we should care - and then provide a methodological and theoretical background for the rest ...

Abstract

For a given population of potential trustees--actors or objects in whom others may seek to place trust--a positive reputation system is a formalized or institutionalized procedure or process by which a particular positive reputation is acquired or lost. Positive reputation systems are common in modern society. Examples include awarding of certifications, awards, credentials, and positive reviews. This study mathematically derives effects of two general characteristics of such systems--how easy it is to get a reputation and how effective the reputation is ...

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Abstract. Economic modeling provides a formal mechanism to understand user incentives and behavior in online systems. In this paper we describe the process of building a parameterized economic model of user contributed ratings in an online movie recommender system. We constructed a theoretical model to formalize our initial understanding of the system, and collected survey and behavioral data to calibrate an empirical model. This model explains 34% of the variation in user rating behavior.We found that while economic modeling in this domain requires an initial understanding of user behavior

Abstract

The new social media sites -- blogs, wikis, Flickr and Digg, among others -- underscore the transformation of the Web to a participatory medium in which users are actively creating, evaluating and distributing information. Digg is a social news aggregator which allows users to submit links to, vote on and discuss news stories. Each day Digg selects a handful of stories to feature on its front page. Rather than rely on the opinion of a few editors, Digg aggregates opinions of thousands of its users to decide ...

Abstract

How do we come to trust our knowledge of the world? What are the means by which we distinguish true from false accounts? Why do we credit one observational statement over another? In _A Social History of Truth_, Shapin engages these universal questions through an elegant recreation of a crucial period in the history of early modern science: the social world of gentlemen-philosophers in seventeenth- century England. Steven Shapin paints a vivid picture of the relations between gentlemanly culture and scientific practice. He argues that problems of credibility in ...

Abstract

In the offline world, we look to the people we trust and those they trust for reliable information. In this paper, we present a computational model of this phenomenon and show how it can be used to identify high quality content in an Open Rating System, i.e., a system in which any user can rate content. We present a case study (Epinions.com) of a system based on this model and describe a new platform called PeopleNet for harnessing this phenomenon in an open distributed fashion. ...

Abstract

The credit system is used to reward users contributing to the network, i.e. uploading to other clients. The strict queue system in eMule is based on the waiting time a user has spent in the queue. The credit system provides a major modifier to this waiting time by taking the upload and download between the two clients into consideration. The more a user uploads to a client the faster he advances in this client's queue. ...

Abstract

Darwinian evolution has to provide an explanation for cooperative behaviour. Theories of cooperation are based on kin selection (dependent on genetic relatedness), group selection and reciprocal altruism. The idea of reciprocal altruism usually involves direct reciprocity: repeated encounters between the same individuals allow for the return of an altruistic act by the recipient. Here we present a new theoretical framework, which is based on indirect ...

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Abstract Recommender systems (RS) have been used for suggesting items (movies, books, songs, etc.) that users might like. RSs compute a user similarity between users and use it as a weight for the usersrsquo ratings. However they have many weaknesses, such as sparseness, cold start and vulnerability to attacks. We assert that these weaknesses can be alleviated using a Trust-aware system that takes into account the ldquoweb of trustrdquo provided by every user. Specifically, we analyze data from the popular Internet web site

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Abstract Recommender Systems allow people to find the resources they need by making use of the experiences and opinions of their nearest neighbours. Costly annotations by experts are replaced by a distributed process where the users take the initiative. While the collaborative approach enables the collection of a vast amount of data, a new issue arises: the quality assessment. The elicitation of trust values among users, termed ldquoweb of trustrdquo, allows a twofold enhancement of Recommender Systems. Firstly, the filtering process can

Abstract

Collaborative Filtering (CF) systems have been researched for over a decade as a tool to deal with information overload. At the heart of these systems are the algorithms which generate the predictions and recommendations.In this article we empirically demonstrate that two of the most acclaimed CF recommendation algorithms have flaws that result in a dramatically unacceptable user experience.In response, we introduce a new Belief Distribution Algorithm that overcomes these flaws and provides substantially richer user modeling. The Belief Distribution Algorithm retains ...

Abstract

Reputation systems provide an incentive for cooperation in artificial societies by keeping track of the behavior of autonomous entities. The self-organization of P2P systems demands for the distribution of the reputation system to the autonomous entities themselves. They may cooperate by issuing recommendations of other entities’ trustworthiness. The recipient of a recommendation has to assess its truthfulness and consistency before taking it into account. The current assessment methods are based on plausibility considerations that have several inherent limitations. In our previous ...

Abstract

George Orwell's prophetic, nightmarish vision of "Negative Utopia" is timelier than ever-and its warnings more powerful. ...

Abstract

Recommender Systems allow people to find the resources they need by making use of the experiences and opinions of their nearest neighbours. Costly annotations by experts are replaced by a distributed process where the users take the initiative. While the collaborative approach enables the collection of a vast amount of data, a new issue arises: the quality assessment. The elicitation of trust values among users, termed ldquoweb of trustrdquo, allows a twofold enhancement of Recommender Systems. Firstly, the filtering process can ...

Note (first note only)

Very interesting book. Very basic, not a single formula. And with a lot of real life facts such as "on Dec 23, 1932, Erdos entered in the house of his friend blabla and he said bla bla bla ...". Attractive way of getting the reader interested.

Abstract

In societal-scale decision-making systems the collective is faced with the problem of ensuring that the derived group decision is in accord with the collective's intention. In modern systems, political institutions have instatiated representative forms of decision-making to ensure that every individual in the society has a participatory voice in the decision-making behavior of the whole--even if only indirectly through representation. An agent-based simulation demonstrates that in modern representative systems, as the ratio of representatives increases, there exists an exponential decrease in the ability for the group to behave in ...

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I wrote it ;-)

Abstract

Many researchers have focussed their efforts in developing collaborative recommender systems. It has been proved that the use of collaboration in such systems improves its performance, but what is not known is how this collaboration is done and what is more important, how it has to be done in order to optimise the information exchange. The collaborative relationships in recommender systems can be represented as a social network. In this paper we propose several measures to analyse collaboration ... ...

Abstract

A critical look at more than one million bloggers and the individual entries of some 25,000 blogs reveals blogger demographics, friendships, and activity patterns over time. ...

Abstract

Recommender systems have proven to be an important response to the information overload problem, by providing users with more proactive and personalized information services. And collaborative filtering techniques have proven to be an vital component of many such recommender systems as they facilitate the generation of high-quality recom-mendations by leveraging the preferences of communities of similar users. In this paper we suggest that the traditional emphasis on user similarity may be overstated. We argue that additional factors have an important role ...

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They cite me ;-)

Abstract

The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said objectively about the relative importance of Web pages. This paper describes PageRank, a method for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them. We compare PageRank to an idealized random Web surfer. We show how to efficiently compute PageRank for large... ...

Note (first note only)

The paper introducing PageRank, the algo behind Google. A simple yet incredibly powerful idea!

Abstract

A network of people connected by directed ratings or trust scores, and a model for propagating those trust scores, is a fundamental building block in many of today's most successful e-commerce and recommendation systems. In eBay, such a model of trust has significant influence on the price an item may command. In Epinions (epinions.com), conclusions drawn from the web of trust are linked to many behaviors of the system, including decisions on items to which each user is exposed. We develop a... ...

Note (first note only)

Maybe the only paper considering distrust. Very interesting early work.

Abstract

In the offline world, we look to the people we trust and those they trust for reliable information. In this paper, we present a computational model of this phenomenon and show how it can be used to identify high quality content in an Open Rating System, i.e., a system in which any user can rate content. We present a case study (Epinions.com) of a system based on this model and describe a new platform called PeopleNet for harnessing this phenomenon in an open distributed fashion. ...

Note (first note only)

Great article, analyzing also the trust-aware part of Epinions.com.

Abstract

An abstract is not available. ...

Note (first note only)

I should re-read it because i forgot it and at that time there was no citeulike!! ;-)

Abstract

Correlation between nodes is found to be a common and important property in many complex networks. Here we investigate degree correlations of the Barabasi-Albert (BA) Scale-Free model with both analytical results and simulations, and find two neighboring regions, a disassortative one for low degrees and a neutral one for high degrees. The average degree of the neighbors of a randomly picked node is expected to diverge in the limit of infinite network size. As an generalization of the concept of correlation, we also study the correlations of other ...

Note (first note only)

TO_BE_READ

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My PhD proposal. Best paper ever! ;-)

Trust-aware decentralized Recommender systems

Note (first note only)

Great paper! It proposes Appleseed, a great trust metric and compares it with Advogato. Attention is given to attacks and attack-resistance. Great paper!

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First paper dealing with trust metrics. Levien created http://advogato.org in order to test his hypothesis. Check the advogato trust metric at http://www.advogato.org/trust-metric.html

Abstract

Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks. ...

Note (first note only)

WOW. long and deep review. more than 40 pages and more than 400 references.

Abstract

We propose and study a set of algorithms for discovering community structure in networks -- natural divisions of network nodes into densely connected subgroups. Our algorithms all share two definitive features: first, they involve iterative removal of edges from the network to split it into communities, the edges removed being identified using one of a number of possible "betweenness" measures, and second, these measures are, crucially, recalculated after each removal. We also propose a measure for the strength of the community structure found by our algorithms, which gives ...

Note (first note only)

TO BE READ